CS1520 Project 1- Search algorithms and symbol tables Solved

To gain a better understanding of search algorithms and symbol tables by implementing an autocompletion engine.

Background
 

In order to make typing on a mobile device quick and easy, an autocomplete feature is commonly implemented to try to guess what word a user wishes to type before they are finished. Such a feature requires extensive use of search algorithms.

Specifications
 Your Box folder contains a copy of the English dictionary that you will use for this project, named dictionary.txt

You must implement a De La Briandais (DLB) trie data structure (as described in lecture) to use in your project.

 When your program is run, it should first create a new DLB trie and add all of the words in dictionary.txt to that trie (this will be the dictionary trie).

 Once the dictionary trie is established, you should prompt the user to start typing a word. For this project, you will be writing only a simple program to demonstrate autocomplete functionality. Due to complexities with gathering single character input in Java, you should accept a single character at a time, each followed by Enter . After each character, present the user with the list of predictions of the word that they are trying to type.

   If the user types a number (1-5), you should consider the user to have selected the corresponding prediction, and restart the process for a new word. Consider $ to be a terminator character; if the user enters a $ , consider the characters input so far to be the full word as intended (regardless of suggestions). Finally, if the user enters a ! at any point, your program should exit.

   To generate the list of predictions, your program should not only consult the dictionary trie, but also keep track of what words the user has entered in the past. If the user has previously entered the same sequence of characters as a prefix to a word, you should prioritize the words that most frequently resulted from this sequence previously. If the user has never entered the current sequence before, or has entered fewer than 5 words with the current sequence as a prefix (i.e., not enough words to complete the list of 5 predictions), your program should suggest words from dictionary.txt that have the current sequence as a prefix.

  You program should propose at most 5 suggestions at a time. If there are fewer than 5 suggestions available from the user’s history and the dictionary trie combined, then only print out the available suggestions.

 If the current sequence of characters has not been entered by the user before and does not appear in dictionary.txt , you should display a message to the user stating that no predicions were found,

 and allow the user to continue entering characters one at a time. Once the user enters a $ , you should consider the word to be finished and add it to the user’s history so that you can predict it in the future.

  Your program should run in a case sensitive manner in order to allow for easier prediction of proper nouns and acronyms.

   The design of the data structure that keeps track of a user’s previously entered words is entirely up to you. You must create a file named approach.txt that both describes your approach to implementing this symbol table and justifies your decision to take this approach. Note that this file does not need to be extensive, just a few lines so the TA is aware of what to look for in your code and why you chose this approach.

   The history of the user’s entered words should persist across runs of your program. To enable this, your program should save a representation of this data structure to the file user_history.txt before exiting.

  Do not add this file to your Box folder! It should be generated by your program.

   Each time the user enters a character, you should use Java’s System.nanoTime() to calculate how long your program takes to find the predictions. You should display this time along with the list of predictions.

   After the user enters ! , your program should output the average time that was required to produce a list of predictions.

An example run of the program would proceed as follows:

 

 

(0.000251 s) Predictions:

(1) t    (2) ta    (3) tab    (4) tab's    (5) tabbed    

Enter the next character:  h               

(0.000159 s) Predictions:

(1) thalami    (2) thalamus    (3) thalamus's    (4) thalidomide    (5) thalidomide's

    

Enter the next character:  e

(0.000052 s) Predictions:

(1) the    (2) theater    (3) theater's    (4) theatergoer    (5) theatergoer's    

Enter the next character:  r

(0.000225 s) Predictions:

(1) therapeutic    (2) therapeutically    (3) therapeutics    (4) therapeutics's    (

5) therapies    

Enter the next character:  e

(0.000182 s) Predictions:

(1) there    (2) there's    (3) thereabout    (4) thereabouts    (5) thereafter    

Enter the next character:  3

 WORD COMPLETED:  thereabout Enter first character of the next word: t

(0.000128 s) Predictions:

(1) thereabout    (2) t    (3) ta    (4) tab    (5) tab's    

Enter the next character:  h

(0.000094 s)